In the Global Navigation Satellite System (GNSS), two measurements are produced: 1) a pseudorange which is a noisy estimate of the full range between receivers and satellites, and 2) a carrier phase which is a much less noisy estimate of the change in range between the receivers and the satellites since the satellites were first tracked. Because the carrier phase only measures the change in range, it has an ambiguity with respect to the full range based on the initial range to the satellite.
When measurements from two receivers are combined in a double difference, the resulting range ambiguity is an integer multiple of the wavelength of the carrier signal. If this integer ambiguity can be correctly resolved, the carrier phase measurements can be used instead of the noisier pseudoranges, improving positioning accuracy. However, if the integer ambiguity is estimated incorrectly, then there will be a large bias in the position estimate. The integer ambiguity estimate must be validated prior to its use in position estimation.
Current methods of carrier phase integer ambiguity validation typically only use a statistical model to validate the quality of the integer ambiguity estimate without testing the actual measurements used to generate the estimate. Such a model-driven approach employs position domain integrity to assure the safety of the position estimate in the presence of potential incorrect integer ambiguity estimates. Such methods, however, do not eliminate the bias from the solution. Rather they only bound the error caused by the bias.